Axient's Systems Engineering Group (SEG) is seeking a Threat and Weapon Systems Engineer to be part of a systems analysis team providing technical contributions and analysis for U.S. Surface Navy (e.g. Aegis Baseline) programs and Missile Defense Agency (MDA) Ballistic Missile Defense System (BMDS) projects. A candidate with MBSE experience is desired (but not required) to support this Model Based Systems Engineering work out of Dahlgren, VA.

Duties will include, but are not limited to:

• Characterize sensor and missile performance against threat ballistic and cruise missiles through modeling, simulation and analysis using digital simulations. Characterize sensitivities to threat variability.
• Develop, integrate and use analytical models and tools to test new threat data and software products, assess system capability, and drive system requirements and design.
• Define technical approach and plan studies based on understanding of engineering community and appreciation of customer need. Define study measures of performance and effectiveness, design experiments, and demonstrate analytical skills. Conduct individual analysis and lead technical studies.
• Communicate with external customer and internal technical staff, via correspondence and briefings.
• Primary technical lead and customer point-of-contact for one or more external customers. Support technical leadership for internal project and contribute in external customer forums. 
• Assist program management in defining future efforts and author technical details of statements of work
• A majority of the work is based out of our Columbia, MD office. Travel is occasionally required to participate in technical forums and reviews.
• Local travel anticipated at 10 percent and occasional overnight trips at 5 percent time. 

Minimum Requirements

• Must be able to obtain and maintain a US DoD security clearance at the required level.  Clearance eligibility requirements include US citizenship.
• Bachelor of Science Degree in Systems Engineering, Aerospace, Mechanical, Electrical, Computer Science, Physics or Applied Math.
• Minimum of 5 years relevant work experience
• Demonstrated systems engineering experience
• Strong analytical skills
• Programming and scripting experience in a Linux environment
• Communication, documentation and briefing via Microsoft office products (Outlook, Powerpoint, Excel, Word)

Desired Qualifications

• Active US DoD security clearance with current investigation
• Masters or PhD degree preferred with relevant research project experience
• MATLAB for the visual display of quantitative information, and prototyping M&S codes
• Python for modeling and simulation development, data analysis, etc.
• Current MBSE experience
• Familiarity working with C++ API and creating test drivers
• Self-starter – Demonstrate independent ownership of tasking. Position affords opportunity to define path and lead tasks based on technical understanding of engineering community and appreciation of customer needs
• Modeling and analysis experience and capability in one or more of the following areas:
  • RF Sensors / EO-IR Imaging / Remote Sensing Systems – Signal Processing, Detection and Track Filtering
  • Multi-Sensor Data Fusion, Target Classification and Discrimination (Machine Learning / AI applications)
  • Missile Systems (Aerodynamic, Ballistic, Space)
  • Defense Weapon System Performance (e.g. Navy Surface systems, Ballistic Missile Defense systems)
  • Ground Test and Field Test Events (missile flight and sensor track pre-event prediction and post-mission assessment)
• Familiarity with version-control (Git), issue tracking (JIRA), collaboration software (Confluence), and cross-language software integration tools (SWIG)
• Familiarity with high-performance computing environments
• Knowledge of aerospace /defense systems technology domains
• Demonstrated experience working with Navy, Air Force, and DoD contractors in a software development environment
• Mathematical background in areas such as statistics, linear algebra, complex analysis, differential equations, Monte Carlo methods, numerical methods, and machine learning (ML) or artificial Intelligence (AI)

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